Joint Resource Allocation and Beamforming Design for BD-RIS-Assisted Wireless-Powered Cooperative Mobile Edge Computing

The wireless-powered mobile edge computing (MEC) has emerged as a promising technique to provide energy supplies and computing services for users in Internet of Things (IoT). However, the limited computational resources and poor channel conditions in traditional wireless-powered MEC systems hinder their ability to meet growing user demands. In this letter, we propose a novel beyond-diagonal reconfigurable intelligent surface (BD-RIS) assisted wireless-powered cooperative MEC model to address these challenges. To maximize the total number of completed task bits, we develop a joint resource allocation and beamforming algorithm based on the penalty and Riemannian trust-region methods to jointly optimize the energy transfer time, transmit power, CPU frequencies of users, bandwidth allocation, and the beamforming of BD-RIS. Simulation results demonstrate that the proposed cooperative computing model significantly improves the total number of completed task bits and highlights the superiority of fully-connected BD-RIS over RIS and simultaneous transmission and reflection RIS (STAR-RIS) in wireless-powered MEC systems.